For hearing aid users, speech-in-noise is one of the most difficult situations to deal with, because the noise deteriorates speech intelligibility. Several methods have been proposed to resolve this issue, but are complicated if the direction of the desired speech is not known, as efforts to reduce the noise can also inadvertently reduce the speech. This inadvertent reduction of the desired speed is called target cancellation and the direction of the desired speech is described by a vector called the steering vector.
Previous methods to resolve the speech-in-noise problem included estimating the steering vector or constraining the adaptation range to avoid target cancellation. The first class of methods that try to estimate the steering vector have significant shortcomings, because the steering vector of different subjects can differ significantly and the steering vector of a single subject is different every time the subject puts on the hearing aid. The second class of methods that limit the adaptation range also has shortcomings, because the limit of the adaptation reduces target cancellation but it also reduces benefit.
A third class of methods does not use a steering vector (indicating a specific target direction), but a range of steering vectors (indicating a target region) where the speech target can come from. This third class of methods uses fixed or adaptive beamforming algorithms (or static and adaptive) to improve the speech intelligibility in noise. Adaptive beamforming algorithms reduce the noise as much as possible with the constraint that sound coming from the target region is not attenuated. Adaptive beamforming algorithms have the highest potential to improve speech intelligibility. This third class of methods that protect the target region work well, but they have been designed for applications that include multiple sensors and that have the capacity for much more computational complexity than found in a hearing aid.
What is needed is an algorithm that does adaptive beamforming, is robust against steering vector mismatches and is computational feasible for a hearing aid.